SKILLEMALL.ai
RU Sign in

AC api-caller

REST API 调用助手。覆盖鉴权（Bearer/API Key/基本认证）、指数退避重试、超时与限流处理、JSON 解析与错误分类、分页与速率控制。当用户需要"调用接口""拉取 API 数据""对接某开放平台""写个请求脚本"时调用。

ClawHub Agent Skills author: qq435912743 v1.0.0 MIT-0 4 files body ≈ 439 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

REST API 调用助手。覆盖鉴权（Bearer/API Key/基本认证）、指数退避重试、超时与限流处理、JSON 解析与错误分类、分页与速率控制。当用户需要"调用接口""拉取 API 数据""对接某开放平台""写个请求脚本"时调用。

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "agent_created"
  • note frontmatter-key unknown frontmatter key "visibility"

Process rating: all ten parameters 58/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 28 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 439 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (4 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 119: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (2 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This skill is a disclosed REST API helper, but users should be careful with its optional local learning log and any API data or tokens they provide.
LLM: benign (medium) · VirusTotal: · 14 Aug 2026